(self, key: str)
| 10467 | return self.path / f"{key}.safetensors" |
| 10468 | |
| 10469 | def load(self, key: str) -> Optional[MTMDEmbedding]: |
| 10470 | entry_path = self._path_for_key(key) |
| 10471 | if not entry_path.exists(): |
| 10472 | return None |
| 10473 | with self._safe_open(entry_path) as tensors: |
| 10474 | metadata = tensors.metadata() |
| 10475 | if metadata.get("version") != self._metadata_version: |
| 10476 | return None |
| 10477 | if metadata.get("model") != self.model_fingerprint: |
| 10478 | return None |
| 10479 | if metadata.get("mmproj") != self.mmproj_fingerprint: |
| 10480 | return None |
| 10481 | embeddings = np.array(tensors.get_tensor("embeddings"), copy=True) |
| 10482 | return MTMDEmbedding(key=key, embeddings=embeddings.astype(np.float32, copy=False)) |
| 10483 | |
| 10484 | def save(self, key: str, embeddings: np.ndarray) -> None: |
| 10485 | if self.max_bytes == 0: |
nothing calls this directly
no test coverage detected